Effect of normalization on statistical and biological interpretation of gene expression profiles.

ABSTRACT: An under-appreciated aspect of the genetic analysis of gene expression is the impact of post-probe level normalization on biological inference. Here we contrast nine different methods for normalization of an Illumina bead-array gene expression profiling dataset consisting of peripheral blood samples from 189 individual participants in the Center for Health Discovery and Well Being study in Atlanta, quantifying differences in the inference of global variance components and covariance of gene expression, as well as the detection of variants that affect transcript abundance (eSNPs). The normalization strategies, all relative to raw log2 measures, include simple mean centering, two modes of transcript-level linear adjustment for technical factors, and for differential immune cell counts, varia

SUBMITTER: Qin S 

PROVIDER: S-EPMC3668151 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature